{"id":"W3158626905","doi":"10.1109/icpr48806.2021.9412463","title":"An Adaptive Model for Face Distortion Correction","year":2021,"lang":"en","type":"article","venue":"","topic":"Advanced Image Processing Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Computer science; Distortion (music); Mobile device; Computer vision; Face (sociological concept); Artificial intelligence; Fidelity; High fidelity; Selfie; Computational photography; Photography; Computer graphics (images); Image (mathematics); Image processing; Telecommunications","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002830949,0.0006016251,0.0005590525,0.000392647,0.0002920776,0.0005120897,0.001280935,0.00084829,0.002205184],"category_scores_gemma":[0.001213544,0.0002903308,0.0007306245,0.0004091509,0.0004727248,0.0006991973,0.0005918432,0.001210584,0.001080623],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005219608,"about_ca_system_score_gemma":0.0006078923,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009221861,"about_ca_topic_score_gemma":0.00753397,"domain_scores_codex":[0.9997124,0.00003757454,0.00001016839,0.00009269593,0.0001043083,0.00004283444],"domain_scores_gemma":[0.9997273,0.00008272481,0.00003799635,0.00003842561,0.00009939348,0.00001408749],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001456529,0.00006873596,0.0009913826,0.00009818939,0.00004043331,0.0001640115,0.00007747778,0.8174682,0.02202119,0.009687434,0.00259376,0.1466435],"study_design_scores_gemma":[0.000003005173,0.00001685213,0.0001269479,0.000002289811,0.000006046025,0.00003413248,0.000003985112,0.9972726,0.001088329,0.0007643316,0.0006761133,0.000005480146],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.007616416,0.0002309537,0.9904772,0.00008696154,0.00005114229,0.00002968556,0.00005035041,0.0002817863,0.001175595],"genre_scores_gemma":[0.7798141,0.0009580681,0.2012772,0.0002088907,0.0001406781,0.0001634022,0.0002808753,0.0001673193,0.01698942],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.009221861,"threshold_uncertainty_score":0.01833636,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03238215593467712,"score_gpt":0.3139207047429017,"score_spread":0.2815385488082246,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}